Fetal loss and long-term maternal morbidity and mortality: A systematic review and meta-analysis

Background Evidence suggests common pathways between pregnancy losses and subsequent long-term maternal morbidity, rendering pregnancy complications an early chronic disease marker. There is a plethora of studies exploring associations between miscarriage and stillbirth with long-term adverse maternal health; however, these data are inconclusive. Methods and findings We systematically searched MEDLINE, EMBASE, AMED, BNI, CINAHL, and the Cochrane Library with relevant keywords and MeSH terms from inception to June 2023 (no language restrictions). We included studies exploring associations between stillbirth or miscarriage and incidence of cardiovascular, malignancy, mental health, other morbidities, and all-cause mortality in women without previous pregnancy loss. Studies reporting short-term morbidity (within a year of loss), case reports, letters, and animal studies were excluded. Study selection and data extraction were performed by 2 independent reviewers. Risk of bias was assessed using the Newcastle Ottawa Scale (NOS) and publication bias with funnel plots. Subgroup analysis explored the effect of recurrent losses on adverse outcomes. Statistical analysis was performed using an inverse variance random effects model and results are reported as risk ratios (RRs) with 95% confidence intervals (CIs) and prediction intervals (PIs) by combining the most adjusted RR, odds ratios (ORs) and hazard ratios (HRs) under the rare outcome assumption. We included 56 observational studies, including 45 in meta-analysis. There were 1,119,815 women who experienced pregnancy loss of whom 951,258 had a miscarriage and 168,557 stillbirth, compared with 11,965,574 women without previous loss. Women with a history of stillbirth had a greater risk of ischaemic heart disease (IHD) RR 1.56, 95% CI [1.30, 1.88]; p < 0.001, 95% PI [0.49 to 5.15]), cerebrovascular (RR 1.71, 95% CI [1.44, 2.03], p < 0.001, 95% PI [1.92, 2.42]), and any circulatory/cardiovascular disease (RR 1.86, 95% CI [1.01, 3.45], p = 0.05, 95% PI [0.74, 4.10]) compared with women without pregnancy loss. There was no evidence of increased risk of cardiovascular disease (IHD: RR 1.11, 95% CI [0.98, 1.27], 95% PI [0.46, 2.76] or cerebrovascular: RR 1.01, 95% CI [0.85, 1.21]) in women experiencing a miscarriage. Only women with a previous stillbirth were more likely to develop type 2 diabetes mellitus (T2DM) (RR: 1.16, 95% CI [1.07 to 2.26]; p < 0.001, 95% PI [1.05, 1.35]). Women with a stillbirth history had an increased risk of developing renal morbidities (RR 1.97, 95% CI [1.51, 2.57], p < 0.001, 95% [1.06, 4.72]) compared with controls. Women with a history of stillbirth had lower risk of breast cancer (RR: 0.80, 95% CI [0.67, 0.96], p-0.02, 95% PI [0.72, 0.93]). There was no evidence of altered risk of other malignancies in women experiencing pregnancy loss compared to controls. There was no evidence of long-term mental illness risk in women with previous pregnancy losses (stillbirth: RR 1.90, 95% CI [0.93, 3.88], 95% PI [0.34, 9.51], miscarriage: RR 1.78, 95% CI [0.88, 3.63], 95% PI [1.13, 4.16]). The main limitations include the potential for confounding due to use of aggregated data with variable degrees of adjustment. Conclusions Our results suggest that women with a history of stillbirth have a greater risk of future cardiovascular disease, T2DM, and renal morbidities. Women experiencing miscarriages, single or multiple, do not seem to have an altered risk.

This paper presents a systematic review with meta-analysis of studies of foetal loss and various maternal outcomes.
I was asked for a statistical report and I interpret that to include all aspects of the design and conduct of the study.

Points of detail
Page 5 Just for the record there is now an updated PRISMA guideline (Page et al., 2021a,b).I suspect any differences are fairly marginal.
Page 5 'The following [. . .] were searched . . .'.The actual database names seem to have gone missing although they are listed in the abstract.
Page 4 tells us that the majority of the cases of stillbirth are in lowand middle-income countries.The existing search revealed few studies in LMICs.Various empirical studies have indicated that the main bibliographic databases have varied and incomplete coverage of material not in English (Pilkington et al., 2005;Shenderovich et al., 2016), and have limited coverage of material from low and middle-income country journals (Kieling et al., 2009;Syed Sheriff et al., 2008).A wider search, for instance in some of the WHO-sponsored ones, might throw up more studies.
Page 5 and 6 The inclusion criteria (page 5) tell us that women with previous experience of loss were excluded but page 6 tells us it was a stratification variable.Does page 5 mean previous history of the outcomes not the types of loss?This needs clarifying.
Page 7 I am not sure that using an arbitrary cut-off for heterogeneity is helpful.As Rücker et al. (2008) have argued it is quite misleading when primary studies are large and give precise estimates.Many of the studies included here had more than a quarter of a million women enrolled which is large by most people's standards.The discussion on page 18 could also benefit from recognising this issue.
Page 9 Perhaps summarise the numbers per country to save the reader having to go through Table 1 and tot them up.The geographical spread is helpful to assess generalisability.the primary studies and a bit more detail about just why they differ so much, the current text is rather cryptic.

Page 12
The sentence starting 'Moreover, endometrial' seems to appear twice.
Page 15 I applaud the caution of stating first to our knowledge but the rest of the discussion occasionally reverts to saying the first.
Page 18 Finding few studies from LMIC seems to me worth mentioning as a limitation here.
Tables 1 and 2 Would these be easier to read if they were in landscape so that more width could be given to some of the columns thus avoiding having studies split over more than one page?
Forest plots The standard RevMan wording 'favours stillbirth' seems to me rather unfortunate as having a higher risk of disease is hardly favourable.
2 Points of more substance 2.1 Some comments on the evidence base It seems to me that there may be more going on in the datasets than is currently presented.To illustrate this I took the first result mentioned in the abstract and did some reanalysis on it.I modelled log risk ratios using inverse variance weighting.I estimated τ 2 using REML and used the Knapp-Hartung adjustment (Knapp and Hartung, 2003).This has been shown to give improved confidence interval coverage (Viechtbauer, 2005).I used the R metafor package in version 3.8-1.

Rates in the control arm
The most striking feature is that the baseline rates vary in the non-stillbirth arm.The largest rate is more than 300 times larger than the smallest.Even if we ignore the two oldest studies on the basis that the world has moved on since 1958 the largest is still more than 100 times the smallest.Having a wide range of situations is obviously a good thing from the point of view of generalisability but there must come a point when it becomes doubtful that the same processes are at work in high incidence settings and low incidence settings.

March 17, 2023
Prediction interval Riley et al. (2011) have suggested that interpretation of random effects models should also incldue a prediction interval.I calculate that a 95% interval is from 0.82 to 3.76 on the risk ratio scale.In contrast to the confidence interval which tells us about the precision with which we have estimated the mean of the distribution of effects the prediction interval tells us where the next study is likely to lie.In this case the prediction interval includes the null value.
Confidence interval for heterogeneity I estimate the 95% confidence interval for τ 2 to stretch from 0.02 to 0.69 which suggests that our estimates here must be regarded as rather uncertain.This obviously affects a random effects model by introducing more uncertainty.
Would risk difference be more appropriate?
There are arguments both for and against using risk difference rather than risk ratio.If we re-analyse using risk difference we find a central estimate of 0.019 with 95% confidence interval from -0.002 to 0.040 which obviousl (just) includes the null value.

What conclusions would I draw?
My feeling from this re-analysis is that the conclusion should be that the evidence base is not yet very strong.I have not examined any of the others.
None of this of course is the authors' fault, we can only meta-analyse what we can find, not what we would have liked to find.

Evidence of absence
In various places the authors seem to suggest that not being able to demonstrate an effect means that there is no effect.This is not the case and those instances would be better re-written as some form of 'We were unable to demonstrate an effect.

Summary
This is a report of a substantial piece of work.The length of my comments should not be interpreted as a value judgment on it but as a justification of my caution in accepting that the case is in any way closed.
health conducted in low and middle-income countries: a survey.BMC Psychiatry, 8(69), 2008.W Viechtbauer. Bias and efficiency of meta-analytic variance estimators in the random-effects model.Journal of Educational and Behavioral Statistics, 30:261-293, 2005.
Page 9 Mean age at loss 23, mean age at follow up 69, mean follow up period 16 years.69 -23 = 46.I can see the figures need not agree exactly but that is a rather large discrepancy.